the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Uncertainties in river basin data at various support scales – Example from Odense Pilot River Basin
Abstract. In environmental modelling studies field data usually have a spatial and temporal scale of support that is different from the one at which models operate. This calls for a methodology for rescaling data uncertainty from one support scale to another. In this paper data uncertainty is assessed for various environmental data types collected for monitoring purposes from the Odense river basin in Denmark by use of literature information, expert judgement and simple data analyses. It is demonstrated how such methodologies can be applied to data that vary in space or time such as precipitation, climate variables, discharge, surface water quality, soil parameters, groundwater abstraction, heads and groundwater quality variables. Data uncertainty is categorised and assessed in terms of probability density functions and temporal or spatial autocorrelation functions. The autocorrelation length scales are crucial when support scale is changing and it is demonstrated how the assumption used when estimating the autocorrelation parameters may limit the applicability of these autocorrelation functions.
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Interactive discussion


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RC S734: 'review', Anonymous Referee #1, 15 Aug 2006
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RC S898: 'Referee comment', Andras Bardossy, 11 Sep 2006
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AC S1481: 'Reply to comments', Jens Christian Refsgaard, 16 Nov 2006
Interactive discussion


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RC S734: 'review', Anonymous Referee #1, 15 Aug 2006
-
RC S898: 'Referee comment', Andras Bardossy, 11 Sep 2006
-
AC S1481: 'Reply to comments', Jens Christian Refsgaard, 16 Nov 2006
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Cited
5 citations as recorded by crossref.
- European case studies supporting the derivation of natural background levels and groundwater threshold values for the protection of dependent ecosystems and human health K. Hinsby et al. 10.1016/j.scitotenv.2008.03.018
- Uncertainty in geological and hydrogeological data B. Nilsson et al. 10.5194/hess-11-1551-2007
- Managing uncertainty in integrated environmental modelling: The UncertWeb framework L. Bastin et al. 10.1016/j.envsoft.2012.02.008
- Identification and Quantification of Uncertainties in a Hydrodynamic River Model Using Expert Opinions J. Warmink et al. 10.1007/s11269-010-9716-7
- Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality H. McMillan et al. 10.1002/hyp.9384